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Title: Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts

Abstract

Uncertainty analysis, reported experimental literature data, and density functional theory were synthesized to model the effect of surface tin coverage on platinum-based catalysts for nonoxidative propane dehydrogenation to propylene. Here, this study tests four different platinum–tin skin surface models as potential catalytic sites, Pt3Sn/Pt(100), PtSn/Pt(100), Pt3Sn/Pt(111), and Pt2Sn/Pt(211), and compares them to the corresponding pure Pt surface sites using an uncertainty analysis methodology that uses BEEF-vdW with its ensembles (BMwE) to generate the uncertainty for the energies of the intermediates and transition states. One experimental data set with two experimental observations, selectivity to propylene and turnover frequency of propylene, was used as a calibration data set to evaluate the impact of the experimental data on informing the models. This study finds that the prior model for Pt3Sn/Pt(100) is the most active and Pt2Sn/Pt(211) is the most selective toward propylene. Active sites on the (100) facet have the highest probability of being responsible for C1 and C2 product formations (C–C bond cleavage). Increasing the Sn coverage on the (100) surface facet to a PtSn/Pt(100) active site leads to a significantly reduced rate and might explain the experimentally observed higher selectivity of Sn-doped catalysts relative to pure Pt catalysts. Next, this studymore » finds that for all surfaces, except PtSn/Pt(100), the rate-controlling steps are the initial dehydrogenation steps alongside some partially rate-controlling second dehydrogenation steps. For PtSn/Pt(100), only the initial terminal dehydrogenation step to CH3CH2CH2* and second dehydrogenation steps are rate-controlling. Next, the calibrated models for all surfaces were found to be selective toward propylene production and model the reported turnover frequency successfully. Nevertheless, Pt2Sn/Pt(211) emerges as the active site with some (minor) evidence as the main active site based on Jeffreys’ scale interpretation of Bayes factors. This observation agrees with prior studies that also found step sites to be most likely the most relevant active sites for pure Pt catalysts. Overall, the results indicate that tin, in addition to affecting the binding strength of the adsorbed species, prevents deeper dehydrogenation (reducing coking) and cracking reactions through increasing activation barriers for unwanted side reactions.« less

Authors:
ORCiD logo [1];  [1];  [1];  [2]; ORCiD logo [2]; ORCiD logo [1]
  1. Univ. of South Carolina, Columbia, SC (United States)
  2. Univ. of North Carolina, Charlotte, NC (United States)
Publication Date:
Research Org.:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Energy Frontier Research Centers (EFRC) (United States). Institute for Cooperative Upcycling of Plastics (iCOUP); Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Basic Energy Sciences (BES); National Science Foundation (NSF)
OSTI Identifier:
1996167
Report Number(s):
LA-UR-23-21983
Journal ID: ISSN 2155-5435
Grant/Contract Number:  
89233218CNA000001; CBET-1534260; 1250052; AC02-05CH11231; 51711
Resource Type:
Accepted Manuscript
Journal Name:
ACS Catalysis
Additional Journal Information:
Journal Volume: 13; Journal Issue: 16; Journal ID: ISSN 2155-5435
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; catalysis; propane dehydrogenation; platinum; tin; uncertainty; Bayesian; density functional theory; microkinetic modeling; platinum-tin catalyst; uncertainty analysis; Bayesian model selection; alkyls; alloys; organic reactions; selectivity

Citation Formats

Fricke, Charles H., Bamidele, Olajide H., Bello, Mubarak, Chowdhury, Jawad, Terejanu, Gabriel, and Heyden, Andreas. Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts. United States: N. p., 2023. Web. doi:10.1021/acscatal.3c00939.
Fricke, Charles H., Bamidele, Olajide H., Bello, Mubarak, Chowdhury, Jawad, Terejanu, Gabriel, & Heyden, Andreas. Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts. United States. https://doi.org/10.1021/acscatal.3c00939
Fricke, Charles H., Bamidele, Olajide H., Bello, Mubarak, Chowdhury, Jawad, Terejanu, Gabriel, and Heyden, Andreas. Mon . "Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts". United States. https://doi.org/10.1021/acscatal.3c00939.
@article{osti_1996167,
title = {Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts},
author = {Fricke, Charles H. and Bamidele, Olajide H. and Bello, Mubarak and Chowdhury, Jawad and Terejanu, Gabriel and Heyden, Andreas},
abstractNote = {Uncertainty analysis, reported experimental literature data, and density functional theory were synthesized to model the effect of surface tin coverage on platinum-based catalysts for nonoxidative propane dehydrogenation to propylene. Here, this study tests four different platinum–tin skin surface models as potential catalytic sites, Pt3Sn/Pt(100), PtSn/Pt(100), Pt3Sn/Pt(111), and Pt2Sn/Pt(211), and compares them to the corresponding pure Pt surface sites using an uncertainty analysis methodology that uses BEEF-vdW with its ensembles (BMwE) to generate the uncertainty for the energies of the intermediates and transition states. One experimental data set with two experimental observations, selectivity to propylene and turnover frequency of propylene, was used as a calibration data set to evaluate the impact of the experimental data on informing the models. This study finds that the prior model for Pt3Sn/Pt(100) is the most active and Pt2Sn/Pt(211) is the most selective toward propylene. Active sites on the (100) facet have the highest probability of being responsible for C1 and C2 product formations (C–C bond cleavage). Increasing the Sn coverage on the (100) surface facet to a PtSn/Pt(100) active site leads to a significantly reduced rate and might explain the experimentally observed higher selectivity of Sn-doped catalysts relative to pure Pt catalysts. Next, this study finds that for all surfaces, except PtSn/Pt(100), the rate-controlling steps are the initial dehydrogenation steps alongside some partially rate-controlling second dehydrogenation steps. For PtSn/Pt(100), only the initial terminal dehydrogenation step to CH3CH2CH2* and second dehydrogenation steps are rate-controlling. Next, the calibrated models for all surfaces were found to be selective toward propylene production and model the reported turnover frequency successfully. Nevertheless, Pt2Sn/Pt(211) emerges as the active site with some (minor) evidence as the main active site based on Jeffreys’ scale interpretation of Bayes factors. This observation agrees with prior studies that also found step sites to be most likely the most relevant active sites for pure Pt catalysts. Overall, the results indicate that tin, in addition to affecting the binding strength of the adsorbed species, prevents deeper dehydrogenation (reducing coking) and cracking reactions through increasing activation barriers for unwanted side reactions.},
doi = {10.1021/acscatal.3c00939},
journal = {ACS Catalysis},
number = 16,
volume = 13,
place = {United States},
year = {Mon Jul 31 00:00:00 EDT 2023},
month = {Mon Jul 31 00:00:00 EDT 2023}
}

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